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Computational-basis measurement weights are squared amplitudes

Statement

Let (∣y⟩)y∈Y be a finite ordered orthonormal computational basis, let ψ=∑y∈Yay∣y⟩ be a unit vector, and put ρ=∣ψ⟩⟨ψ∣. For the computational-basis projective measurement with Py=∣y⟩⟨y∣, the associated POVM weight is

p(y)=tr⁡(ρPy)=∣ay∣2.

In particular these weights are nonnegative and sum to one.

Facts & Assumptions

Given: A finite ordered orthonormal computational basis (∣y⟩)y∈Y and a unit vector ψ=∑yay∣y⟩.

[F1]

Dirac Notation Conversion: ∣u⟩⟨v∣ sends z to ⟨z,v⟩rootu, and the root inner product is linear in its first argument.

[F2]

The computational basis is orthonormal: computational register bases are orthonormal.

[F3]

A unit-vector outer product is a density operator and Density operator: the outer product of a unit vector is a nonnegative trace-one density operator.

[F4]

Finite projective measurements: a finite projective measurement has outcome weights tr⁡(ρPy) for its projections Py.

[F5]

Finite POVMs and their outcome law: a finite POVM assigns the outcome weight tr⁡(ρEy) to effect Ey.

[F6]

The basis-independent trace of an endomorphism of a finite-dimensional vector space: trace is the sum of diagonal matrix entries in any finite-dimensional basis.

Proof

1.1givenF1F2F4F5F6algebra

By [F1] and [F2], Py∣z⟩=δy,z∣y⟩; hence the Py are pairwise orthogonal self-adjoint idempotents and sum to the identity, as can be checked on every basis vector. For z=∑wbw∣w⟩, ⟨Pyz,z⟩root=∣by∣2≥0, so these projections are POVM effects by [F4]–[F5]. Also ⟨y,ψ⟩root=ay‾, so ρPy∣z⟩=0 for z≠y and ρPy∣y⟩=ay‾ψ. The coefficient of ∣y⟩ in this last vector is ∣ay∣2. Thus the only nonzero diagonal entry of ρPy in this basis is ∣ay∣2, and [F6] gives tr⁡(ρPy)=∣ay∣2.

2.1givenF2F3F4F5step 1.1algebra∎

The vector projector ρ is a density operator by [F3]. The computational-basis projective measurement and its associated POVM law [F4]–[F5] therefore assign weight tr⁡(ρPy)=∣ay∣2 to outcome y. Since the basis is orthonormal and ∥ψ∥=1, ∑y∣ay∣2=1; each term is nonnegative. Hence the weights form a probability distribution.

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